AI could transform catastrophe modelling of secondary perils

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<rdf:Description>
<dc:creator>Geer, Joshua </dc:creator>
<dc:date>2025-09-16</dc:date>
<dc:description xml:lang="es">Sumario: Artificial intelligence (AI) and machine learning (ML) are poised to significantly enhance catastrophe modelling for secondary perils, such as severe convective storms, derechos, tornadoes, and wildfires, by leveraging vast amounts of high-resolution atmospheric data. Karen Clark, founder of Karen Clark & Company, emphasized during the Rendez-Vous de Septembre in Monte Carlo that AI and ML can improve forecasting accuracy for events traditionally difficult to predict, like derechos and tornado touchdowns, and can also help model wildfire behavior by analyzing wind patterns that influence fire spread</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/188548.do</dc:identifier>
<dc:language>eng</dc:language>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Catástrofes naturales</dc:subject>
<dc:subject xml:lang="es">Inteligencia artificial</dc:subject>
<dc:subject xml:lang="es">Seguro de riesgos extraordinarios</dc:subject>
<dc:subject xml:lang="es">Machine learning</dc:subject>
<dc:subject xml:lang="es">Modelos predictivos</dc:subject>
<dc:subject xml:lang="es">Riesgos meteorológicos</dc:subject>
<dc:subject xml:lang="es">Incendios</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">AI could transform catastrophe modelling of secondary perils</dc:title>
<dc:relation xml:lang="es">En: Insurance ERM: the online resource for enterprise risk management. - 16 September 2025 ; 1 p.</dc:relation>
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